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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: roberta-gest-pred-seqeval-partialmatch
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# roberta-gest-pred-seqeval-partialmatch
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6909
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- Precision: 0.7952
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- Recall: 0.7778
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- F1: 0.7489
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- Accuracy: 0.8458
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 2.0269 | 1.0 | 147 | 1.2260 | 0.3446 | 0.3571 | 0.3404 | 0.6696 |
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| 1.0422 | 2.0 | 294 | 0.8553 | 0.5596 | 0.5248 | 0.4885 | 0.7594 |
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| 0.7198 | 3.0 | 441 | 0.7086 | 0.6623 | 0.6298 | 0.6110 | 0.8097 |
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| 0.5231 | 4.0 | 588 | 0.6330 | 0.7415 | 0.7102 | 0.7061 | 0.8264 |
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| 0.3947 | 5.0 | 735 | 0.6246 | 0.8023 | 0.7382 | 0.7446 | 0.8345 |
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| 0.2866 | 6.0 | 882 | 0.6487 | 0.8263 | 0.7578 | 0.7496 | 0.8519 |
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| 0.2338 | 7.0 | 1029 | 0.6662 | 0.7970 | 0.7608 | 0.7452 | 0.8465 |
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| 0.1791 | 8.0 | 1176 | 0.6762 | 0.7923 | 0.7690 | 0.7432 | 0.8398 |
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| 0.1495 | 9.0 | 1323 | 0.6496 | 0.8008 | 0.7946 | 0.7686 | 0.8552 |
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| 0.1316 | 10.0 | 1470 | 0.6909 | 0.7952 | 0.7778 | 0.7489 | 0.8458 |
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### Framework versions
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- Transformers 4.27.3
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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